The importance increases proportionally to TF but is offset by IDF. Words that are common in every text, such as stop words (and, the, an, it for instance) have low TFIDF even though they appear many times in texts. For each text, the TFIDF is calculated for individual words in the corpus. Then, each text is represented as a vector of TFIDFs. Vectors are usually normalised to be of length 1. The calculation of TFIDF can be done in several different ways, some of which are described in [1]}, [2]}, [3]}.
